Analysis of community question-answering issues via machine learning and deep learning:State-of-the-art review

Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic interest.Scholars have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the ever-growing volume of content that CQAs engender.To clarify the current state of the CQA literature that has used ML and DL,this paper reports a systematic literature review.The goal is to summarise and synthesise the major themes of CQA research related to(i)questions,(ii)answers and(iii)users.The final review included 133 articles.Dominant research themes include question quality,answer quality,and expert identification.In terms of dataset,some of the most widely studied platforms include Yahoo!Answers,Stack Exchange and Stack Overflow.The scope of most articles was confined to just one platform with few cross-platform investigations.Articles with ML outnumber those with DL.Nonetheless,the use of DL in CQA research is on an upward trajectory.A number of research directions are proposed.

Structure of the Quarks and a New Model of Protons and Neutrons: Answer to Some Open Questions

The described structural model tries to answer some open questions such as: Why do quarks not exist in the open state? Where are the antiparticles from the Big Bang?

The Taiwan Question China From the Perspective of International Crisis Management:History and Future

The Taiwan Question China discussed in this paper belongs to the theoretical crisis discussion on international relations and does not regard the Cross-Strait relations as relations between different countries.The outcome of the 2024 Taiwan Election has a great impact on the Taiwan question,the latest poll shows that the possibility of the Democratic Progressive Party(DPP)candidate to come to power is still very high,because its political evolution trend of Taiwan independence still exists.

MKEAH:Multimodal knowledge extraction and accumulation based on hyperplane embedding for knowledge-based visual question answering

Background External knowledge representations play an essential role in knowledge-based visual question and answering to better understand complex scenarios in the open world.Recent entity-relationship embedding approaches are deficient in representing some complex relations,resulting in a lack of topic-related knowledge and redundancy in topic-irrelevant information.Methods To this end,we propose MKEAH:Multimodal Knowledge Extraction and Accumulation on Hyperplanes.To ensure that the lengths of the feature vectors projected onto the hyperplane compare equally and to filter out sufficient topic-irrelevant information,two losses are proposed to learn the triplet representations from the complementary views:range loss and orthogonal loss.To interpret the capability of extracting topic-related knowledge,we present the Topic Similarity(TS)between topic and entity-relations.Results Experimental results demonstrate the effectiveness of hyperplane embedding for knowledge representation in knowledge-based visual question answering.Our model outperformed state-of-the-art methods by 2.12%and 3.24%on two challenging knowledge-request datasets:OK-VQA and KRVQA,respectively.Conclusions The obvious advantages of our model in TS show that using hyperplane embedding to represent multimodal knowledge can improve its ability to extract topic-related knowledge.

The most important questions in cancer research and clinical oncology Question 2-5.Obesity-related cancers:more questions than answers

Obesity is recognized as the second highest risk factor for cancer. The pathogenic mechanisms underlying tobaccorelated cancers are well characterized and efective programs have led to a decline in smoking and related cancers, but there is a global epidemic of obesity without a clear understanding of how obesity causes cancer. Obesity is heterogeneous, and approximately 25% of obese individuals remain healthy(metabolically healthy obese, MHO), so which fat deposition(subcutaneous versus visceral, adipose versus ectopic) is "malignant"? What is the mechanism of carcinogenesis? Is it by metabolic dysregulation or chronic inflammation? Through which chemokines/genes/signaling pathways does adipose tissue influence carcinogenesis? Can selective inhibition of these pathways uncouple obesity from cancers? Do all obesity related cancers(ORCs) share a molecular signature? Are there common(overlapping) genetic loci that make individuals susceptible to obesity, metabolic syndrome, and cancers? Can we identify precursor lesions of ORCs and will early intervention of high risk individuals alter the natural history? It appears unlikely that the obesity epidemic will be controlled anytime soon; answers to these questions will help to reduce the adverse efect of obesity on human condition.

PAL-BERT:An Improved Question Answering Model

In the field of natural language processing(NLP),there have been various pre-training language models in recent years,with question answering systems gaining significant attention.However,as algorithms,data,and computing power advance,the issue of increasingly larger models and a growing number of parameters has surfaced.Consequently,model training has become more costly and less efficient.To enhance the efficiency and accuracy of the training process while reducing themodel volume,this paper proposes a first-order pruningmodel PAL-BERT based on the ALBERT model according to the characteristics of question-answering(QA)system and language model.Firstly,a first-order network pruning method based on the ALBERT model is designed,and the PAL-BERT model is formed.Then,the parameter optimization strategy of the PAL-BERT model is formulated,and the Mish function was used as an activation function instead of ReLU to improve the performance.Finally,after comparison experiments with traditional deep learning models TextCNN and BiLSTM,it is confirmed that PALBERT is a pruning model compression method that can significantly reduce training time and optimize training efficiency.Compared with traditional models,PAL-BERT significantly improves the NLP task’s performance.

Operational requirements analysis method based on question answering of WEKG

The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challenge is that the existing weapons and equipment data fails to carry out structured knowledge representation, and knowledge navigation based on natural language cannot efficiently support the WEORA. To solve above problem, this research proposes a method based on question answering(QA) of weapons and equipment knowledge graph(WEKG) to construct and navigate the knowledge related to weapons and equipment in the WEORA. This method firstly constructs the WEKG, and builds a neutral network-based QA system over the WEKG by means of semantic parsing for knowledge navigation. Finally, the method is evaluated and a chatbot on the QA system is developed for the WEORA. Our proposed method has good performance in the accuracy and efficiency of searching target knowledge, and can well assist the WEORA.

DPAL-BERT:A Faster and Lighter Question Answering Model

Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering systems.However,with the constant evolution of algorithms,data,and computing power,the increasing size and complexity of these models have led to increased training costs and reduced efficiency.This study aims to minimize the inference time of such models while maintaining computational performance.It also proposes a novel Distillation model for PAL-BERT(DPAL-BERT),specifically,employs knowledge distillation,using the PAL-BERT model as the teacher model to train two student models:DPAL-BERT-Bi and DPAL-BERTC.This research enhances the dataset through techniques such as masking,replacement,and n-gram sampling to optimize knowledge transfer.The experimental results showed that the distilled models greatly outperform models trained from scratch.In addition,although the distilled models exhibit a slight decrease in performance compared to PAL-BERT,they significantly reduce inference time to just 0.25%of the original.This demonstrates the effectiveness of the proposed approach in balancing model performance and efficiency.

The question answer system based on natural language understanding

Automatic Question Answer System(QAS)is a kind of high-powered software system based on Internet.Its key technology is the interrelated technology based on natural language understanding,including the construction of knowledge base and corpus,the Word Segmentation and POS Tagging of text,the Grammatical Analysis and Semantic Analysis of sentences etc.This thesis dissertated mainly the denotation of knowledge-information based on semantic network in QAS,the stochastic syntax-parse model named LSF of knowledge-information in QAS,the structure and constitution of QAS.And the LSF model's parameters were exercised,which proved that they were feasible.At the same time,through "the limited-domain QAS" which was exploited for banks by us,these technologies were proved effective and propagable.

On Answering the Question Related to the Legal Regulation of Working Hours in the New Era:Western Experience and Chinese Approach

The popularity of flexible working hours around the world has slowed down the historical trend of reducing working hours.It even shows signs of regression.Whether and how to guide the cur-rent society with flexible working hours to return to the historical track of reducing working hours,improve the quality of working hours,and promote a smooth transition from the era of traditional standard work-ing hours to the era of flexible working hours has become a question related to the legal regulation of working hours in the new era.In this regard,although Western countries have proposed new regulatory concepts and carried out legislative practices with distinctive charac-teristics,the limitations of legal regulation capabilities have prevented them from proposing a package of institutional solutions.The advan-tage of China in the ability of legal regulation of working hours has been gradually formed in the legislation on working hours unnder the leadership of the CPC in the past century.It enables China to break through the limitations of the West and propose a Chinese approach to answer the question of the legal regulation of working hours in the new era from three aspects:limiting the extension of working hours,improving the quality of flexible working hours,and optimizing the funnctions of the multi-funnctional regulatory system for working hours.

Gender Differences In Using Questions——An Investigation of the Questions Used by Mr. Rochester and Jane in Jane Eyre

In literature,differences in the description of female and male characters have been noticeable for a long time.In this study,the novel Jane Eyre is uses as a material to investigate whether there are in fact any significant differences in the questions Mr.Rochester and Jane use and how the questions function to portray these two main characters.

Query Expansion Based on Semantics and Statistics in Chinese Question Answering System

In Chinese question answering system, because there is more semantic relation in questions than that in query words, the precision can be improved by expanding query while using natural language questions to retrieve documents. This paper proposes a new approach to query expansion based on semantics and statistics Firstly automatic relevance feedback method is used to generate a candidate expansion word set. Then the expanded query words are selected from the set based on the semantic similarity and seman- tic relevancy between the candidate words and the original words. Experiments show the new approach is effective for Web retrieval and out-performs the conventional expansion approaches.

Fatigue sensation following peripheral viral infection is triggered by neuroinflammation: who will answer these questions?

Fatigue is best defined as difficulty in initiating or sustaining voluntary activities, and is thought to be accompanied by deterioration of performance. Fatigue can be caused by many factors such as physical and mental stress, disturbance in the circadian rhythm, and various diseases. For example, following the flu or other types of infections, everyone has experienced a sense of fatigue that can last for days or weeks. The fatigue sensation is thought to be one of the signals for the body to suppress physical activity in order to regain health. The mechanism of induction of the fatigue sensation following viral infection has not been well understood. Although fatigue was once thought to be caused by fever, our recent study with an animal model of viral infection demonstrated that the fatigue sensation is caused not by fever, but rather,

Design of Questions in the Teaching of English Reading

Questions which were conventionally designed to check reading comprehension can also be used to enhance understanding. Different types of questions can be designed to achieve different purposes in reading. While designing questions, teachers should take into consideration such points as the language used, manner of presentation and types of questions etc. Moreover, once questions have been designed, it’s essential for teachers to think about the techniques for the use of these questions. If appro- priately used, questions contribute greatly to students’ understanding of what they’ re reading by helping to explore the meaning that language conveys, in addition to developing proper reading skills. Therefore, teachers should be able to teach reading with well-designed questions so that the ultimate goal of understanding the text is likely to be achieved.

A Study on Teacher's Questioning Strategies in the UK

Classroom questioning is one of the main means for classroom interaction which plays a very important role in classroom teaching. Therefore, based on the observation of four different level English classes in the UK and interview of English teachers, this thesis investigates the types, functions and answer-seeking strategies used by EFL teachers.

Design of Text-based Questions from the Study of Typology of Questions

Questions can be classified from different perspectives： grammatical form, communicative value, content orientation and cognitive level. In language pedagogy, text-based questioning as both an attention drawing device and a form of learning tasks serves text instruction. Therefore, language teachers preparing text-based questioning should take into consideration all dimensions of questions, especially cognitive requirement and communicative character. In addition, interaction between learner, text and the world can be achieved by the adoption of both about-the-text and beyond-the-text questions in teachers＇ text-based question construction.

Expert Recommendation in Community Question Answering via Heterogeneous Content Network Embedding

ExpertRecommendation(ER)aims to identify domain experts with high expertise and willingness to provide answers to questions in Community Question Answering(CQA)web services.How to model questions and users in the heterogeneous content network is critical to this task.Most traditional methods focus on modeling questions and users based on the textual content left in the community while ignoring the structural properties of heterogeneous CQA networks and always suffering from textual data sparsity issues.Recent approaches take advantage of structural proximities between nodes and attempt to fuse the textual content of nodes for modeling.However,they often fail to distinguish the nodes’personalized preferences and only consider the textual content of a part of the nodes in network embedding learning,while ignoring the semantic relevance of nodes.In this paper,we propose a novel framework that jointly considers the structural proximity relations and textual semantic relevance to model users and questions more comprehensively.Specifically,we learn topology-based embeddings through a hierarchical attentive network learning strategy,in which the proximity information and the personalized preference of nodes are encoded and preserved.Meanwhile,we utilize the node’s textual content and the text correlation between adjacent nodes to build the content-based embedding through a meta-context-aware skip-gram model.In addition,the user’s relative answer quality is incorporated to promote the ranking performance.Experimental results show that our proposed framework consistently and significantly outperforms the state-of-the-art baselines on three real-world datasets by taking the deep semantic understanding and structural feature learning together.The performance of the proposed work is analyzed in terms of MRR,P@K,and MAP and is proven to be more advanced than the existing methodologies.

The Role of Questioning in the Teaching of Reading

In learner-centered classroom,teachers' questioning serves as very important stimuli to foster students' participation in classroom interaction.A classroom full of active interactions is an ideal environment for foreign language acquisition(FLA).Questioning is a critical strategy for the instructors to engage students in reading activities so as to help them build the habit of independent learning.

The most important questions in cancer research and clinical oncology

Specific research foci:(1) Mouse models of gamma-herpes virus-68(γHV-68) and polyomavirus(Py V) infections during neonatal versus adult life.(2) For human papilloma virus(HPV)-positive oropharyngeal carcinoma(OPC)—(a) Asking the question: Is oral sex a powerful carcinogen?(b) Examining the evidence for the vertical transmission of HPV infection.(c) Examining the relationship between HPV and Epstein–Barr virus(EBV) infections and nasopharyngeal cancer(NPC) in West European, East European, and East Asian countries.(d) Examining the association between HPVpositive OPC and human leukocyte antigen(HLA).(3) For non-smoking East Asian female lung adenocarcinoma—(a) Examining the incidence trends of HPV-positive OPC and female lung adenocarcinoma according to birth cohorts.(b) Examining the association between female lung adenocarcinoma and HPV.(c) Examining the associations of lung adenocarcinoma with immune modulating factors.(4) For triple-negative breast carcinoma(TNBC) in East Asians—(a) Examining the association between TNBC and HPV.(b) Examining the unique epidemiological characteristics of patients with TNBC. A summary "epidemiological" model tying some of these findings together.

The Land Question and Catholic-Anglican Relations in Buha, Western Tanzania： The White Fathers and C.M.S. Experience, 1934-1959

Land was important--in the course of spreading and seeking new converts--for both Missionaries of Africa （White Fathers） and Church Missionary Society （C.M.S.） in Buha, Western Tanzania. This paper examines the land question as one of the challenges that the White Fathers encountered in their attempt to evangelize communities in Western Tanzania. I argue that the land question remained throughout the late-colonial period one of the unresolved issues, and at some mission stations, impeded the activities of the White Fathers and C.M.S. missionaries. This paper relies on archival documents first, to examine the land question and White Fathers-C.M.S. relations in Buha from 1934 to 1959. Second, I intend to demonstrate the fact that land issues remained at the heart of the missionary enterprise in Buha. Both Catholic and Anglican missionaries were determined to have more mission plots for medical, education and religious purposes.